Rationale The Program in Implementation Science has created a series of courses within the Training in Clinical Research Program that are designed to meet the didactic training needs of fellows and junior faculty, but lacks an experiential component.  To be effective, implementation research must accommodate the unique culture and context that define specific health care settings and communities.  An “Action Research” Program can help meet this need—which involves partnering with health care providers to improve their own practices, which in turn will enhance their working environment.  Action research’s strength lies in its focus on generating solutions to practical problems and its ability to empower health care providers, by getting them to engage with research and the subsequent development or implementation activities.  We propose an action research program to achieve at least 3 broad goals:

1. To design innovative strategies to improve health care delivery or public/community health in real-time in San Francisco by capitalizing on the experience and skills of an interdisciplinary team of UCSF implementation scientists... the goal of which is to improve health and care delivery in targeted settings using strategies that are designed to be patient-centered and to reduce total health care costs.

2. To provide a hands-on training and implementation experience for students, residents and fellows by involving them in a real-world project through all stages of development... the goal of which is to attract/encourage students to pursue careers committed to improving health care delivery, system redesign and community health programs.

3. To design an action research program that can be self-sustaining through reimbursements from stakeholder organizations and delivery systems who directly benefit financially from the impact of the action research program.

Plan

We request pilot funds for 1 year to develop and implement this program at UCSF.  It will consist broadly of 8 steps that culminate with the initial launch of a delivery system intervention. 

Step 1. Select a Partner with a “Hot Spot”. Hot spots are problem areas in clinical operations, quality or health outcomes that are identified by stakeholders (such as payors, administrators, providers or patients) as priority areas for intervention.  In our first cycle, we will focus on UCSF Medical Center ambulatory practices.  To identify potential partners, we will invite practice chiefs and administrative directors of these practices to submit brief, 1-page descriptions of Hot Spots in their practice that they would like the action research program team to help them intervene on.  Key criteria will include feasibilty of measuring and intervening on Hot Spot, engagement of clinic providers/staff, learner access to relevant data, staff, patients and providers, and degree to which addressing hot spot will help improve quality, reduce health care costs and enhance the patient experience.

Step 2.  Assemble Action Team.  Advertise volunteer/training opportunities to students and residents in medicine, pharmacy, nursing and dentistry.  Commitment of 2-4 hours per week for 4-6 months is required.  Limit to 6-8 students.  Identify key content/strategy experts from UCSF faculty and partners.

Step 3. Characterize Hot Spot with existing data sources.  Further characterize with administrative and/or medical record data to examine frequency, distribution, variability and predictors of the key process or outcome that represents the Hot Spot.

Step 4.  Conduct Literature Review of Hot Spot.  This will be performed by a combination of faculty and students.  Medical students will apply some of the principles taught in their EEBM (Epidemiology and Evidence Based Medicine) classes.

Step 5. Convene Launch Meeting and Design Workshop.  This will be a 1 or 2 day retreat in which the partner clinic (and staff) are brought together with the faculty and students on the Action Team.  The goal of the meeting will be to create a timetable with specific activities benchmarks for completing the project in a 4-6 month time frame.

Step 6. Conduct & Analyze Formative Research.  Interviews and observations will be performed to gain a greater understanding of the patient, provider, staff and system-level factors that contribute to the Hot Spot being investigated.  With close guidance from faculty, students will be charged with collecting and analyzing this data.

Step 7. Create Alpha-Version of Intervention Approach.  Combine data inputs from the literature review, the quantitative analysis of administrative/EMR data, and the formative research findings to design an intervention approach. 

Step 8. Launch First Iteration (Beta-Version) of Intervention; Collect Process Data

Criteria and metrics for success

1. Submission of Hot Spot proposals from multiple clinics—shows interest/need for service.
2. Requests to participate from multiple students/residents—shows interest/appeal to trainees.
3. Implementation of intervention that has a significant impact (>10-20% change from baseline) on Hot Spot measure.
4. Explicit plan for continued monitoring and refinement of intervention by participating clinic.

Total Budget: $70,904

Salary support for principal faculty and part-time research assistant.

Collaborators: Ralph Gonzales (Medicine); Margaret Handley (Epidemiology & Biostatistics); Sara Ackerman (Medicine); Joshua Adler (Chief Medical Officer; UCSF Medical Center)

Rationale: An effective randomization system is crucial to the design, conduct, and analysis of any randomized controlled trial (RCT).  Despite the apparent ease of flipping a coin (either literally or with a computer algorithm), designing a reliable randomization system that meets the design, statistical and logistical requirements for real-world use in an RCT is a major challenge.  Multicenter critical care studies, for example, typically require extremely rapid access to a centralized system (24 hours/day), for randomization of time-sensitive interventions, while maintaining blinding and balanced recruitment between treatment arms and entry criteria strata.  Large scale NIH and industry funded trials can invest in designing, building and hosting web-based randomization systems that accomplish these goals, but the costs of doing this are prohibitive for smaller trials with more constrained budgets. The design and implementation of a state-of-the-art randomization system that could be made available to the global research community at very low cost would facilitate the conduct of properly designed and blinded RCTs and remove an important barrier to the conduct of interventional research.

One commentor gave us 2 web sites that were already set up to do what we had proposed. Thanks for the referrals. We were not aware of them before and had not found them on our search.

These are indeed usable platforms for randomizing patients in clinical trials. I have tested them out and they provide just the system that we were proposing to create. The prices are not unreasonable either: one system is better for smaller studies (http://www.randomizer.at)(start up cost is $600 for first 50 enrollees and then $5/ additional enrollee; the other system (http://www.randomize.net/) has a flat fee of $2500 and is independent of the size of the enrollment (good for large studies).

It would be a good idea if the CTSI could post these web addresses on the CTSI web site resource page to alert investigators that there are inexpensive randomizer sites available for their studies.

We will withdraw our proposal.

Rationale.  Problem: because of multiscale complexity, conceptual, mechanism-based, in vitro-to-in vivo mapping models are hard to falsify and can be flawed in ways that may not be obvious until challenged experimentally, which can be costly.  When the results of such experiments are equivocal or not supportive, the information needed to revise mechanistic hypotheses may be lacking.  Translation of in vitro phenomena to in vivo counterparts requires a mapping model.  Currently, mechanism-agnostic correlation models are common.  When translation is based on hypotheses about underlying mechanisms, the mapping model is almost always conceptual, often described in prose, supported by diagrams and, occasionally, mathematical models.  Solution: explicitly instantiate mechanistic mapping models in silico and explore their feasibility.  We envision concrete, computational, observable-in-action, experimentally challengeable mapping models that will evolve to become executable knowledge embodiments showing what does and does not translate under specific conditions.

The concept is illustrated in a recent paper (PMID: 20406856), “Tracing multiscale mechanisms of drug disposition in normal and diseased livers.”  We used, improved, and revalidated a multiscale in silico liver (ISL).  An ISL is an example of a new class of computational models.  We posited that changes in micromechanistic details from normal to diseased ISLs may have disease-causing, hepatic counterparts.  Together, the ISL and in silico methods represent an important step toward unraveling the complex influences of disease on drug disposition.  We demonstrated translating—morphing—a validated “normal” ISL into a “diseased” ISL.  Although ISLs are abstract software constructs, that transformation stands as a concrete, mechanistic hypothesis about what does and does not translate from one to the other.  The methods, which are new and novel, are designed to be extensible to whole organisms and, eventually, patients.  Being able to transform one validated ISL into another is important: it is evidence that the approach can be used to explore and challenge ideas about translation, making translational research more concrete. 

We envision “translational models” showing how, for example, in silico micromechanistic details are morphed between analogues of in vitro rat and human hepatocyte cultures, and in time between in vitro computational analogues and human analogues.  The morphing process will show what must be added and what is lost in translation.  A long-range goal for such morphings will be to provide an easily understood, mechanistic interpretation of how cause-effect relationships resulting from an experimental intervention in a wet-lab model are believed to manifest (or not) in a human analogue.  The expectation is that those relationships will have real world counterparts. 

Plan.  An essential precondition for achieving the above vision is to have two different, biologically related models (e.g., in vitro & in vivo) that have independently achieved validation targets.  We will focus on the above-cited ISLs and improved versions of in silico hepatocyte (ISH) cultures (PMID: 21768275): we will focus on translation of phenomena measured in hepatocyte cultures to corresponding, location dependent phenomena within hepatic lobules in rat and human livers.  We have designed the models so that hepatocytes can be exchanged: ISHs that have achieved validation targets under different culture conditions (ongoing during year one) can be plugged into an ISL (after its hepatocytes are removed).  The iterative refinement needed to reestablish whole-liver validation targets (including intralobular zonation) will provide a concrete theory of mechanistic attributes gained and lost in translation. 

Criteria and metrics for success.  1) Instantiation of quasi-autonomous ISH objects and documentation (a conference paper, e.g., the Winter Simulation Conference) that they can be transferred from one context (a simulated culture) to another (a simulated lobule) while retaining all the mechanistic features validated in vitro.  2) Produce a draft manuscript that demonstrates that an ISL with these new hepatocytes can also achieve whole liver phenomena, such as zonation of enzyme induction.  Produce a draft manuscript by year’s end for submission within the following four months. 

Approximate cost and brief justification.  Achieving 1 & 2 above will require several hundred cycles of iterative refinement (1 postdoc @ $48K working full time with Dr. Hunt) of in silico components (described in PMID: 20406856).  Simulation, publication, and meeting costs bring the total to $58K. 

Collaborators. Jackie Maher, UCSF Liver Center

Rationale: The purpose of this application is to strengthen the tuberculosis (TB) translational research capacity at UCSF/SFGH by developing a BSL-3 laboratory in which work with human TB can be safely carried out in tissue culture and in small animal models.  Such work will enable us to extend observations that we have made in molecular epidemiological studies of TB in San Francisco, permit new lab-based investigation in the context of existing, funded clinical studies in San Francisco and abroad, and facilitate additional studies in animal models of infection. Having such a facility will enable us to examine immunological responses to as well as the pathogenicity and virulence of clinical strains of M. tuberculosis (M.tb) isolated from patients in San Francisco and in other areas across the US and globally, and to study the impact of co-infections with M.tb and other pathogens (e.g., HIV). We have a superb multidisciplinary group of investigators working in the US as well as in Kenya, Tanzania, Zimbabwe, Uganda, and Vietnam in studies of the transmission and pathogenesis of TB. In a number of these studies, observations have been made that suggest differences among strains and interactions between specific strains and hosts of specific race/ethnicity. Examination of these findings in lab-based studies and/or in an animal model will, if confirmed, enable back translation to human studies and approaches to vaccine and drug development. The availability of a new BSL-3 will facilitate the work of investigators working across many disciplines and enable questions to be addressed that can only be examined in animal models. Given the international scope of existing research activities, this effort will also mesh with efforts at UCSF and SFGH to enhance global health. In recent efforts to recruit an investigator focused on TB immunology, the major limiting factor has been the lack of BSL-3 space. Thus, having such a facility is a critical element in filling a critical deficiency in our TB research program.

Plan: Although a BSL-3 laboratory exists in Building 100 at SFGH, this laboratory is heavily utilized, inadequately designed, and not amenable to the maintenance of M. tb infected animals. Other alternatives have been carefully explored but deemed not feasible for reasons of experimental protocol, safety, and/or cost. We propose to upgrade an existing BSL-2 laboratory in Building 3, a seismically sound building, to BSL-3 status. Based on input from the construction firm that built the existing space, the total cost of the build-out of the BSL3 is estimated to be $1.2M. There is widespread enthusiasm and broad support to create such a facility, as indicated by commitments that total $950,000 from a consortium of funders including the Department of Medicine, the Medical Service at SFGH, the SFGH Dean's Office, and the Ireland Fund, but there remains a $250,000 deficit. We are asking for $100,000 to help leverage these commitments. Given our success in raising the needed funds, we are confident that the additional $150,000 will be secured, even if it means obtaining a loan that would be paid back by users over time.

Criteria and Metrics for Success: The single metric will be the hiring of one independent TB immunology investigator by 2013. The Division of Experimental Medicine will commit the resources for at least one start-up package to hire faculty members focused on the immunology of human TB. Each package would include at least $1M in start-up funds and the provision of BSL1 and BSL2 space ensuring that, if the BSL-3 is built, the criterion of success will be met.

Approximate Cost and Justification: We are requesting $100,000, an amount that will be combined with additional resources that have already been committed (see above). These aggregated funds will be used to purchase or construct: 1) animal holding space with self-contained cage ventilated racks for mice or guinea pigs; 2) several biosafety cabinets for the safe handling of M.tb in tissue culture; 3) autoclave alcove to house the autoclave and the CO₂ gas manifold; 4) clean vestibule (entrance and exit); 5) dirty vestibule (entrance to both of the laboratories and the animal holding room); and 6) ultralow freezer for storage of bacterial stocks and infected tissues. The space will have the mechanical system required for a completely independent ventilation system.

Faculty who would use this facility: Hopewell, Havlir, Kato-Maeda, Catamanchi, Davis, Metcalfe, Nahid, Everett, Cox, McCune, Nixon

Rationale:  Inaccurate sample size estimation leads to research studies that enroll too few or too many study participants. The former can result in failure to demonstrate anticipated effects and the latter to excessive costs, due to overuse of research participants and personnel time. While there are several important components of a good sample size calculation – including a compelling research question, an appropriate outcome variable, and an efficient study design – here we focus on improving the accuracy of the quantitative inputs. Examples of such parameters include:  

• the variability of responses within and between eligible participants (accounting for correlations among replicate measurements at a given time and/or at different times),  
• the mean response under standard-of-care conditions, and
• the prevalence of the disease under study.

At present, the primary sources of parameter values are pilot studies (often too small to provide reliable estimates) and published studies (which often lack the needed values). Estimates of parameter values that are not evidence-based can introduce a large amount of error into the sample-size calculation, making it precise but inaccurate. The proposed web-based application would allow a clinician and biostatistician to identify required values in real time during a consulting visit, revising the query as needed to ensure a viable and cost-efficient study.  Given the enormous number of medical studies launched every year, access to accurate inputs to sample size calculations could vastly reduce waste of valuable resources.

Plan: The two key ingredients to obtaining a wide range of evidence-based inputs for sample size calculations are the availability of electronic sources of current health information and a convenient means of retrieving relevant information from the databases. During pilot funding, we will demonstrate feasibility of (1) identifying relevant existing databases; (2) quantifying improved accuracy of sample-size calculations based on of evidence-based parameters (as defined here) relative to those based on other sources of inputs; and (3) producing version 1 of a user-friendly web-based interface to access, summarize, and output evidence-based parameters in useful formats. Beyond pilot funding, additional databases could be tapped, and the breadth of access, summarization, and output could be expanded. 

Aim 1:  Identify Databases:

• Ideal databases should provide longitudinally tracked individual-level health outcomes related to a wide range of conditions. Two excellent examples appear to be (1) Databases included in the UCSF CTSI Large Dataset Inventory, accessible at no cost through http://accelerate.ucsf.edu/research/celdac.  (Example: National Health Interview Survey) (2) The Kaiser healthcare database. [Must: Identify key personnel who could provide access, engage their interest, and establish an agreement to collaborate.]

• With clinical partners: Establish a set of commonly expected requests that could be used to evaluate candidate databases on quality and availability of desired data.  
• With database partners and computer experts: Optimize access to and manual retrieval of information.

Aim 2:  Proof of Concept  

• Identify commonly used outcome variables and alternative choices through review of the published literature and discussion with clinical colleagues.
• Identify a selection of recently published high-profile studies that reported the values of key study design parameters. For each: (1)  Document the eligibility criteria and parameter values that were used in the study design. (2) Document corresponding values drawn from the selected databases. (3) Examine the effect on the sample size of differences between the two sets of parameter values.
  

Aim 3: Create a web-based user interface, a manual of procedures with useful examples, and useful export files.

• User experience:

          o   Make retrieval fully dynamic: any outcome stored in the database; retrieval tailored to major eligibility criteria (e.g., age and diagnosis) and design criteria (e.g., frequency of assessment per patient).

          o   Use drop-down menus, populated by database-specific data dictionaries, to ensure accurate spelling.

          o   Produce results that are easy for the investigator or biostatistician to manipulate. The software will process all (or a random sample of) eligible values to generate rates (see example appended), means, variances, and correlations, as needed. 

          o   Generate downloadable documentation of queries for user’s later access.

• Developer experience:

         o   As queries of a database are made, record queries (including search criteria) and results.

         o   Identify unavailable measures; examine reasons. Automate or prompt search for an alternative database and/or measure.

Criteria and metrics for success:

Aim 1:  Compare the proposed database resources in terms of features, data quality, and costs: 

• Are Common Data Elements used?
• Is a data dictionary available for sorting and browsing to find measures available?
• Does resource have the requested measures?
• How current are the measures?

Aim 2:  For a range of recently published studies that reported the values of key study design parameters, evaluate the effect on the sample-size calculation of differences between reported parameter values and values retrieved from our proposed database resource(s).  Hypothesis:  Evidence-based values will modify the sample size calculation by at least 10%.   

Aim 3:  Compare the proposed database resource(s) in terms of ease of access and value of information gained: 

• Poll users to obtain feedback on ease of use and value of information retrieved, by database.  
• Summarize measures queried by frequency. 
• Characterize variation among databases with respect to comprehensiveness and ease of use.
• Estimate personnel costs associated with building database access.

Cost:  We seek funding to access at least two large free databases by leveraging the CTSI Large Database Inventory [Aim 1], to quantify the benefit of evidence-based parameter values on sample-size calculations [Aim 2], and to plan the computational work in fine detail [Aim 3].  Salary support $100,000 (12 months) for principal faculty and staff.

Collaborators: Joan Hilton (Epidemiology & Biostatistics) will lead the biostatistical aspects of the “App” development.  Tracy van Nunnery (Medicine) will lead a team of computer experts who will create the database interfaces. Kirsten Bibbins-Domingo (Medicine) will serve as lead clinical collaborator.

Example interface and output:  Dr Hilton and Mr Nunnery have on-going research collaborations that began in 2007. Mr. Nunnery and his team created HERO, the electronic medical record system used at Ward 86 of SFGH, and thus are well acquainted with HIPAA requirements. As an example of their work, users (clinicians) can query HERO to obtain the distribution of any patient characteristic captured by clinicians, limited to user-specified search criteria. The web-based interface for retrieving demographic data is shown below, with the date fields displayed (upper image).  The distributions of demographic characteristics were exported to an Excel spreadsheet (lower image).

The Challenging Path from Bench to Bedside
Although basic and clinical scientists have long collaborated, translational research challenges investigators to move beyond the traditional training of both laboratory scientists and clinicians. The delivery of effective clinical solutions involve the integration of science, technology, intellectual property, market analysis, product development, clinical, regulatory and reimbursement strategy, and marketing. These are clearly very different disciplines and functions, practiced by professionals with very different backgrounds and experiences. Nevertheless, early investigators benefit tremendously from an appreciation for how these various factors affect the likelihood that an innovation will successfully lead to clinical implementation. In the T1 Catalyst Program at UCSF CTSI, we work closely with investigators to identify and support key innovations that are likely candidates for translation. Common concerns and questions about the many challenges in translating basic research toward clinical practice are routinely discussed.

A Video-Based Initiative to Trigger Early Engagement and Collaboration
We propose the production and targeted distribution of a series of brief (3-5 minutes) professional videos to broaden the dissemination of this information, and highlight UCSF and external resources available to support investigators tackle these challenges. The videos will illustrate a number of case studies through engaging narratives of the experiences and challenges faced by investigators, administrators, and business professionals at UCSF and private organizations. The impact of each case study will be further bolstered by highlighting the stories of the ultimate beneficiaries of successful translational research - patients.

This pilot project will focus on five key topics: needs assessment, intellectual property, strategic partnerships, getting to first-in-human clinical trials, and regulatory strategy. These videos will not provide in-depth analyses of each subject, but be a catalyst for viewers to assess their own needs, discover available resources, seek further information or assistance, and share their thoughts and ideas. Within UCSF, we will also highlight the expertise at the Office of Technology Management (OTM), the Office of Innovation, Technology and Alliances (ITA), the Institute of Quantitative Biosciences (QB3), and others to provide a more complete view of the resources available to investigators. Our objectives are: (i) to inform interested UCSF investigators of the key challenges to translational research, (ii) to persuade them that UCSF (and its partners) can support them to be successful; and (iii) to inform external organizations that UCSF is a valuable partner for translational research and development.

Leveraging Storytelling, Consumer-Generated Content and Social Networking
To maximize reach and impact, the videos will tell a number of stories, that weave together the many facets of translational research. These will not be instructional videos. They may include dramatized re-enactments, and character development that convey the many, often opposing, objectives of stakeholders. The videos will be hosted and promoted through traditional and non-traditional distribution channels that not only target public and private investigators, but their research assistants, and supporting administrators. This wider audience will be encouraged to participate in the narrative by providing feedback or sharing videos of their own experiences and concerns. These discussions will be further promoted to increase awareness and a sense of community and shared interest.

We will also coordinate promotion with other UCSF and UC communication channels (i.e. UCTV, etc.), as well as several external business and R&D groups. Distribution efforts may also include targeted email marketing, other CTSA network communication channels, outreach to relevant bloggers, etc. The outreach will be accompanied by viewer analytics to improve and customize future projects and campaigns.

Assessing Awareness and Long-Term Engagement
In the short term, we will measure the success of our project through viewer surveys. These surveys will be carefully designed to elicit information about the viewer's understanding of why and how translational research occurs, their interest in learning more, and ongoing concerns. In the long term, we will use the results from our outreach-based analytics, and measures of increased interest from UCSF and non-UCSF investigators and business professionals, to assess the impact of this project (e.g. measured through the number and quality of applications to the T1 Catalyst Award Program).

An Experienced and Multi-Disciplinary Team
The project will be a collaborative effort between CTSI's Communications team and Early Translational Research (ETR) program. John Daigre and Katja Reuter (CTSI Communications) are experienced multimedia and social media professionals who will serve as advisors throughout the planning, production, and editing process, and take a leading role in the promotion phase. ITA, OTM, QB3 and other key UCSF-based institutions will also be major contributors to the project. An external video production company will be hired to help develop story lines, and produce and edit the videos. Ruben Rathnasingham (ETR), who has helped develop a number of university-based innovations into clinical products, will manage the project.

Total Budget: $40,000 

This pilot project will take 6 months to complete with a budget of $40,000 for planning, production, editing, and promotion. 

Rational:

CTSI’s Consultation Services Data Management Unit (DMU) is just one of the successful research resources available on campus to help UCSF faculty and staff with his/her research.  Along with many other data management services, the DMU also provides consultation in data processing to help transform research data into a statistically analyzable format.  In our efforts to provide consultation to the UCSF research community, we have realized that some trainees and faculty do not have the programming skills or resources to perform data processing tasks that are necessary to keep their research moving forward.  Complicated data merges and transformations require specific programming expertise to ensure that it is performed correctly.  Data management programmers, who can devote more time and effort to small projects, are needed.  The DMU’s ability to provide these services is very limited.  As a result, we have identified a gap in services that the Data Management Unit is currently able to provide.   

All research requires some level of data management programming.  This expertise exists far and wide across campus. Regrettably, there is not an easy way to identify these experts.  Our goal is to form a community of data managers on campus.  The purpose of this community would be to 1.) identify specific data management programming expertise across campus, 2.) pool resources by sharing job descriptions, computer programs, workflow processes and standard operating procedures, and 3.) identify data managers who are able to provide services on a short-term, variable-effort basis.     

Data management programming is an integral step in preparing research results. Expanding access to data management services that include programming will greatly impact the efficiency, accuracy, and productivity of research at UCSF.  By leaving complicated programming tasks to the experts, researchers will be able to spend more time writing grants and developing manuscripts.

Plan: 

Most data managers on campus are in the Analyst, Programmer Analyst or Biostatistician job title category.   With the help of UCSF’s Operational Excellence Human Resources group we would first survey all UCSF staff within these job classifications to find data manager and biostatistical programmers who would fit well into our Data Management for Research Community.   The two main inclusion criteria would include those with 1) data management/programming expertise and 2) who work in a research environment.  Those who fit the criteria will be invited to join the Data Management for Research Community.  Membership would provide access to data management resources and a subscription to a quarterly Data Management for Research Community newsletter.  In return, we would require that each person fill out a brief Data Management questionnaire to help identify his/her data management expertise as well as a follow-up questionnaire to assess satisfaction with becoming a member.  Specifically, the Data Management questionnaire would ask questions regarding the programmers area of research and UCSF department, level of experience in working with large national databases, clinical trials, observational studies, cross-sectional studies, etc., and level of expertise in various data management and statistical programs, including SQL, VisualBasic, FoxPro, MSAccess, SAS, Stata, SPSS, excel, etc.  We would also ask questions regarding his/her preference for different levels of engagement, such as, email, conference call and/or in person meetings.  Through this process we hope to create a network of managers/programmers who are able to work with the DMU, an inventory of data management resources, and opportunities for providing data management services on a short-term, variable-effort basis to those who need it.    

Total Budget: $25,343  

A 20% Analyst I for 12 months will be needed to survey staff, set up the questionnaire in RedCap and compile/store inventory of resources.  A 5% Programmer Analyst for 12 months will provide content to the newsletter and design the questionnaires. 

Criteria and Metrics of Success:  Number of data management programmers identified, overall response rate, rate of membership enrollment, inventory of data management resources, number of data managers who are able to provide services and satisfaction with membership.

Collaborators:

Janet Coffman, MA, MPP, PhD and CELDAC,
Laura Bettencourt and the San Francisco Coordinating Center

Joe Hesse, Department of Neurology

Rationale – The mammalian gastrointestinal (GI) tract contains hundreds of distinct species of commensal microbes under normal conditions, referred to as the ‘microbiota’.  Recently, it has been appreciated that the microbiota exists in a mutualistic relationship with the host immune system. Mutations affecting the production of certain cytokines or resulting in the lack of immune cell subsets are known to increase the overall bacterial burden; however, how underlying immunological conditions influence the colonization of specific species of commensal microbes is poorly understood.  PhyloChip, a recently innovated DNA microarray, is able to rapidly identify over 60,000 microbial taxa in samples of interest.  Using this techonology, we can ascertain the exact effects of diverse immunological phenotypes on the microbiota of the GI tract. Currently, these chips are used extensively at UCSF by the lab of Susan Lynch, though their use has thus far been limited to particular diseases and related environmental studies. We believe that the development of a microbial database encompassing many different immunological states is necessary to better understand the true relationship between GI microbiota and the host immune system. Our first aim is to dissect the unique feature of the ‘microbial profile’ (fluctuation of specific microbial species) in fecal samples obtained from various mouse models of disease including: virus infection, malignancy, arthritis, colitis, asthma, dermatitis and diabetes, as well as genetically modified mice with impairments in immune factors such as cytokines, chemokines, transcription factors and variety of immune receptors (a vast number of them are available in the UCSF mouse inventory). Second, we will compile this information and build the Microbial Database as a web-based open resource for the scientific community. Gathering a microbial profile from each disease state or immunological phenotype will allow us to predict the impact of immune perturbations on the specific make-up of the microbiota and the potential impact on disease.  This project is also an attempt to investigate the potential of PhyloChip as a novel diagnostic and prophylactic tool.       

Plan – We propose following step1 to 3 to accomplish this pilot study.         

Step1 - Standardize the sample collection.  The use of mice provides some stability in terms of mouse to mouse variation.  However, commensal microbiota is very sensitive to age, sex, diet and the environment in each animal facility.  To minimize these confounding effects, we will employ co-housing method.  The mice of interest (designated as tester mice which are genetically modified or disease mice) will be housed in the same cage with control mice (which are wild-type B6 mice raised in our animal facility).  In the case of infectious disease models, tester mice will be orally administered with the feces homogenate collected from control mice before infection.  This method will equilibrate the microbiota in gastrointestinal tract and allow us to dissect the pure influence of specific gene or disease on the colonization of microbial species.  

Step2 - Analyze by PhyloChip.  As a pilot experiment, we will collect fecal samples from 20~30 of the most commonly used genetically-modified mice maintained in our lab or available in UCSF mouse inventory (Rag1-/-, Rag2Il2rg-/-, mMt, b2m-/-, MHCII-/-, Tcra-/-, Tcrg-/-, Lta-/-, Fas-/-, Cd28-/-, Dap10-/-, Dap12-/-, Myd88-/-, Trif-/-, Ifnar1-/-, Il2-/-, Il4-/-, Il6-/-, Il10-/-, Il12rb-/-, Il15-/-, Il17ra-/-, Foxp3-DTR) and major experimental disease models studied in our lab or neighbor labs (Carcinogen-induced tumor, Experimental colitis, Type I diabetes, Listeria infection, Cytomegalovirus infection, Influenza infection, OVA-induced asthma).  All samples will be processed by PhyloChip and we will perform comparative and phylogenetic analysis to reveal the effect of immunity on the all level of microbe’s taxon. 

Step3 - Build pilot database.  All accumulated data will be computationally reconstituted.  We aim to build the data browser with which users can interactively explore the microbiota profile for particular gene or disease. 

Criteria and Metrics for success – 1) Identification of the unique microbial profile in each sample.  2) Launch microbial database.  We will share our data with other researchers all over the world who are interested in the microbiology and immunology, and will accept their feedback and suggestions to improve user-friendliness.  Once these criteria are met, we will move to scale up the size of database.  We will collect samples from another ~50 genetically-modified mouse strains and accept samples from other collaborators.  Ultimately, our approach can be applied into human diseases. 

Estimated cost - We are requesting $40,000 for a pilot study (Step1 and 2).  To build-up public database, we will need $30,000.  For scale-up database, it will need $30,000.

Collaborators - Shoko Iwai (Susan Lynch lab, Dept. of Medicine)

Rationale:  Enrolling subjects for longitudinal research studies, ensuring their compliance and retaining them over a period of time pose a significant challenge to researchers. As an example, we had 62% and 30% retention at years 1 and 3 in a recently concluded study on knee osteoarthritis. To overcome these challenges and to optimize workflow associated with data acquisition, quantification, we have developed a design which combines multiple computing platforms to create a seamless, user-friendly experience for all participants (researcher and subject).  The platforms [using  Ruby on Rails (RoR),  PostgreSQL, iOS  and representational state transfer (RESTful) API]  are designed to enable researchers and subjects to complete data acquisition forms and surveys on tablets which then get quantified and submitted to our cloud servers. Qualitative data show improved subject satisfaction compared to paper forms, reduced paper use by researchers and study coordinators, reduction in man-hours by researchers and study coordinators to manually quantify survey scores and input data into the database and better quality control.

Based on these initial experiences using mobile technology for enhancing subject’s participatory experience and streamlining associated workflow, we propose – (1) the expansion of our current platform to UCSF Imaging clinics (for recruitment and improving care experience), (2)  a one year research study on obese individuals examining effect of weight-loss on knee tissue health using quantitative imaging. This will enable us to analyze the efficacy of the platform towards maintaining compliance and increasing retention. (3) Additionally, we also intend to pilot a networked module incorporating social gaming and feedback principles to assess behavior modification in this population which is of special interest to our lab for our research on knee osteoarthritis prevention.

PLAN:  Recruitment component: (1) Over the 1^st three months, enhance the current tablet computer applications to include    interactive versions of intake forms, standardized questionnaires, as well as, modules which simulate the procedure to be performed (MRI, CT, radiography) to address common issues like claustrophobia, restricting movement during scanning etc.. This module will also offer the patients to learn about unique capabilities of the UCSF Imaging centers (safety regulations, metal suppression sequences, quantitative imaging capabilities, other research studies which offer volunteer opportunities) along with a brief bios of the personnel who will be interacting with the patients during their procedures.  While the patients learn about the UCSF imaging capabilities, they will have the option to explore ongoing research participation opportunities  and, if interested, sign up to be contacted by a study coordinator. We have multiple longitudinal trials underway at the moment which will benefit from this mode of recruitment. Possibility of using mHealth frameworks implemented at UCSF will be explored to allow for future adaptability across other UCSF departments. (2) Over months 3-9, administer the tablets to all patients at the UCSF imaging centers (Orthopedic Institute, China Basin Landing and Mission Bay) scheduled for musculoskeletal imaging for clinical or research purposes.

Retention and gaming component: (1) Over months 4-12, twenty-five adult obese subjects from the UCSF- Weight Management Program will be recruited. These subjects will undergo MR imaging at baseline and 6 months, 9 months for quantification of knee tissue health using our standardized metrics. At each time point, subjects will complete surveys related to their levels of physical activity, nutritional data, and incidence of musculoskeletal pain/injuries every month. Additionally, the subjects will complete surveys  remotely using mobile applications (described later) every 6 weeks. (2) Over the 1^st three months, develop mobile phone applications for surveys and a “gamified” feature where the research participants can track their scores (levels of physical activity, functional status, pain status, calorie intake) and compare it to other participants, promoting increased participation of physical activity using competitive motivation. A virtual character will be designed (eg: an alien trying to reach home planet) and the participant  will need to complete all study associated tasks, as well as, maintain a certain level of physical activity, consume the recommended diet to enable the character to succeed at the game. Periodically, information on the benefits of the interventions will be incorporated, feedback on the performance with resulting improvements will also be provided and quizzes on weight-management will be incorporated. These approaches have been shown to be effective in management of diabetes, improving physical activity in children and improving walking capacity in adults to cite a few (1-3).

Long term plan: This pilot will be used to demonstrate feasibility, efficacy and flexibility of the platform using UCSF Imaging clinics and research. In the next phase, an NIH application will be submitted for a larger, longer research project where the platform will be implement in obese individuals undergoing surgical and non-surgical weight-loss and followed-up for four years. Eventually, the platform will be made available to all UCSF researchers interested. Recruitment and clinic modules will be made available to other interested UCSF departments immediately. 

Criteria and metrics for success: (1) Percentage of participants enrolled in research studies from the UCSF imaging centers (currently unknown) (2) Clinic patients and research participants will be invited to complete an online survey assessing their satisfaction with their experience, likelihood to stay in the research study and likelihood to return to UCSF for future appointments. (3) Retention in the research studies over a one year period will be compared to retention in all of our other longitudinal studies. (4) Impact of weight-loss on changes in composition of knee articular and meniscal cartilage using quantitative imaging, intramuscular fat content of thigh muscles, levels of physical activity, amount of weight-loss will be assessed at one year.

Approximate Costs and Justification: Total Budget = $95,350; 2 Tablet computers for development @ $400 ea. = $800; 20 Tablet computers for deployment @ $400 ea.    = $8,000; 15% effort from the PD/PI  (Dr. Kumar)  = $8,550; 25% effort from QUIP-C software developer over the year = $25,000; Consultant fees for gamification of the applications =  $25,000; Partial costs for MR imaging of research participants (shared with other grants)  = $28,000

Collaborators:  Deepak Kumar (MQIR); Vivek Swarnakar (QUIP-C), Sharmila Majumdar( MQIR), MQIR), David Dean ( QUIP-C), Richard Souza (MQIR), TBD(Game developer)  

REFERENCES:

1)      Aoki N, Ohta S, Masuda H, Naito T, Sawai T, Nishida K, Okada T, Oishi M, Iwasawa Y, Toyomasu K, Hira K, Fukui T. Edutainment tools for initial education of type-1 diabetes mellitus: initial diabetes education with fun. Stud Health Technol Inform. 2004;107(Pt 2):855-9.     

2)      Southard DR, Southard BH. Promoting physical activity in children with MetaKenkoh. Clin Invest Med. 2006. 29(5):293-7.

3)      Consolvo S, Everitt K, Smith I, Landay JA. Design requirements for technologies that encourage physical activity. In: Grinter R, Rodden T, Aoki P, Cutrell E, Jeffries R, Olson G, editors. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems; 2006 Apr 22-27; Montreal, Quebec, Canada. New York: ACM; 2006. p. 457-66.

Rational: There is extensive evidence of pervasive social disparities in health, many of which take root in early life. The importance of early childhood in setting the stage for future health and social outcomes is buttressed by rigorous scientific studies across disciplines. However, what remains less investigated is how well this knowledge has been translated to public agencies responsible for implementing early childhood programs and family support services. The Department of Children Youth and their Families (DCYF) in San Francisco is one of the few departments in the country dedicated exclusively to meeting the needs of young people, and has made extensive investments in child physical and mental health programming and family support services (over 11 million dollars in 2010). However, the effectiveness of these programs in influencing key social, mental and physical health outcomes has not been investigated.  Through a collaborative effort of UCSF researchers, the San Francisco Mayor’s Office, the Department of Children Youth and their Families (DCYF), the San Francisco Department of Public Health (SFDPH), and the San Francisco Unified School District (SFUSD), we propose to develop a linked administrative data system that will allow us to track and evaluate the impact of early childhood programming and family support services on academic achievement, and mental and physical health.

Plan: We propose to develop a data linkage between the DCYF and SFUSD systems, with the goal that this linkage will be generalizable to other agencies serving youth in San Francisco.  The goals for this proposal are to 1) assess similarities and differences in existing data structures used by DCYF and SFUSD, 2) address confidentiality issues related to establishing a linked data system in San Francisco, and 3) select and test linkage variables that will uniquely identify individual level information across DCYF and SFUSD datasets. Dr. Kaja LeWinn, a social epidemiologist in the Department of Psychiatry, will play a key role in this effort. Dr. LeWinn has spent the last two years working closely with SFUSD, has developed an intimate knowledge of the school-based services provided by DCYF and existing tracking systems, and has established relationships with key partners.  To accomplish our goals, our group with meet every other month for the duration of the award and Dr. LeWinn will meet individually with specific members as necessary.

Criteria and Metrics of Successes: At the end of this pilot project year, we will have developed a reliable linkage between the DCYF and SFUSD data systems, and submitted an application for grant support to further develop and implement this system.

Cost: We ask for $20,000 to provide salary support for Dr. LeWinn so she may dedicate research time to further developing this project and relationships with key public sector collaborators.

Collaborators: Our collaboration is united around the common vision that physical and mental health disparities begin early in life, and that a longitudinal, linked data system that tracks the usage and effectiveness of publically available programs will be an instrumental resource for both researchers and public policy makers. Key public sector collaborators and supporters include: the Mayor’s Office (represented by Hydra Mendoza); Richard Carranza, Deputy Superintendent for Instruction, Innovation and Social Justice, SFUSD; Maria Su, Director of the Department of Children Youth and Their Families; and Ritu Khanna, Assistant Superintendent, Research Planning and Accountability, SFUSD. Dr. LeWinn will play a key role in maintaining this partnership in collaboration with Orlando Elizondo, Director of the SFUSD/UCSF Partnership.  

Rationale: The rapidly evolving field of digital health has great potential to enhance biomedical research, education and clinical care. Development in this new space is largely being driven by the tech sector, where projects may lack proper clinical focus or scientific rigor and generally do not include health outcome measures to assess effectiveness or impact. UCSF can play a vital role in ensuring that digital health ideas are appropriately targeted to real clinical problems and that they result in meaningful impact, by improving health, improving care, and lowering costs. We propose the i2i Translational Digital Health Program to foster UCSF and industry collaborations to initiate, develop, and test impactful and cost-effective digital technology to improve biomedical research, education, and clinical care.

Plan: This i2i proposal is to identify and develop the critical resources and programs necessary to facilitate and accelerate the “idea to impact” trajectory for digital health innovators both within and outside UCSF, in a multidisciplinary way that combines sound scientific methods with technology, design, business strategy, fundraising, IP, regulatory and marketing expertise. This first year of i2i will focus on the following:

1. Establish a focal point for CTSI Digital Health initiatives, with multidisciplinary internal/external partners
   • Create an intersection for collaboration between UCSF Digital Health initiatives (e.g., BMI, ISU, QB3, ITA, SOM, Institute for Reducing Health Care Costs and other innovative efforts at UCSF).
   • Create strong UCSF presence in Digital Health to external partners, working with Virtual Home on a website, with campus on social media, with Development officer, etc.
   • Explore and establish external partnerships (e.g., UCs, CITRIS, investors, companies, public health).
   • Host Annual UCSF Digital Health Summit: to showcase “ideas” and “impacts,” convene partners
2. Identify and implement needed processes and resources for accelerating “idea to impact”for the main types of digital health projects, e.g., projects aiming for a) internal (e.g., RAP) and external grants; b) operational deployment to improve health locally to globally; and c) commercialization. We will:
   • Convene a series of meetings with faculty/trainees, staff, and various external partners (e.g., investors, tech companies, start-up incubators, design firms, etc.) to define hurdles, needs, objectives
   • Work with ITA and other groups to define models for supporting each type of project, and implement initial steps with FAQs, standard agreements, etc. as appropriate
3. Build a vibrant and supportive Digital Health i2i community
   • Establish an external Digital Health consultant panel, modeled after T1 Catalyst, to serve as consultants to UCSF, grant reviewers on RAP proposals, i2i Advisors, etc., with networking events
   • Establish an internal consultant panel of research, clinical, education, technology, and informatics experts to serve as consultants grant reviewers, Services, i2i Advisors
   • i2i Web presence - with Virtual Home, enhance UCSF Profiles (digital health keywords), Digital Heath Innovators Forum, links to useful collaboration tools, survey needed resources, crowdsourcing i2i tips
   • Quarterly or bi-monthly multidisciplinary “Eye to Eye” roundtables featuring specific research or clinical “problems” and potential digital “solutions,” presented to an audience of External and Internal Panel members, to foster relationships and potentially ignite Digital Health projects.
4. Define and implement recharge and IP models for internal and external consultation We will work with Consultation Services, ETR, ITA, etc. to adapt and develop processes for UCSF faculty consulting to industry, for industry consulting to faculty/staff, and for staff (e.g., ISU, ITA) consulting to faculty

Criteria and Metrics of Success: digital health website with communications plan and metrics; defined internal pathway/processes for idea transfer; implemented recharge mechanism for Consultation Services; 20 external consultants panel members, from range of disciplines and public/private; 15 internal consultants panel members; Annual Summit, 4 “Eye to Eye” events; 2 new external partnerships

Cost and justification: Staff support 0.4 FTE $40,000K; website and communications: $20K; Symposium and “Eye to Eye” roundtables: $10,000 with sponsorships to defray; external consultants panel $5,000.

Total: $75,000. The sustainability model will include recharge, shared royalty/licensing programs, partnerships with clinical enterprise/external groups, UCSF Digital Health Consulting Panel (to external parties), and philanthropy, with self-sustainability anticipated in 3 years.

Collaborators: Sim/Sawyer (BMI), Lee (ETR), Pletcher (CS), Yuan (Virtual Home), Lium (ITA), Melese (SOM), Crawford (QB3), Jorgenson (ISU)

Rationale: The APEX system has been promoted to the faculty as providing a new and extremely valuable means of doing clinical research, especially for discovering previously unappreciated clinical associations such as the relationship of kidney stone and myocardial infarction, etc..  Such associations would be very valuable in discovering underlying mechanisms of disease.  However, the APEX system falls very short of fulfilling this promise, because it has been primarily designed for maintaining information for medical practice, and for billing.  The problem is that it forces the physician to use vague descriptors of disease that are so imprecise as to be of no value whatever in discovery of associations.  For example in our Lipid Clinic we have discovered a form of dyslipidemia, cholesterol 7 alpha hydroxylase deficiency, that we believe afflicts about 100,000 Americans.  The APEX system refuses to allow us to enter this diagnosis for search purposes, insisting on “cholesterol problem” as a substitute.  Because there are probably fifty individual diagnoses that could fall under this heading, all value to translational research is lost.

Also there are data from emerging biomarkers, etc. that it will not accept for search processes. An example is the biomarker, prebeta-1 HDL, also discovered by our group, which is emerging as a robust indicator of risk of myocardial infarction. We have measured this biomarker on nearly four thousand patients.  We should be able to enter it  with  the restriction that it cannot be used for clinical decision making, but allowing faculty to access its value for clinical research.

An academician from the Cleveland Clinic, lecturing here recently, stated they also found APEX nearly useless for research, leading them to re-engineer the IT to overcome these issues, making detailed information searchable.  This was done carefully within the envelope of APEX without altering its function for clinical practice, billing, etc.

Plan: We would bring in expert IT personnel to make the changes in APEX, fitting it to our particular needs and system characteristics at UCSF.  We would support part-time effort of a clinical faculty member to supervise the entry of appropriate descriptors, following the experience at the Cleveland Clinic.

Criteria and Metric:

We can test the system for association of descriptors in widely diverse information fields.

Approximate cost:

Expert IT consultation and engineering $40K

Faculty time for descriptors: $ 15K

Collaborators:  Faculty from diverse disciplines would be welcomed to bring precision to the descriptors in their respective fields.

Background/Rationale: Social networking sites such as Facebook, Google+ and LinkedIn are web platforms. They allow independent applications to run within their sites to enhance the user experience, often integrating with external services to provide dynamic content as varied as reading lists from Amazon, blog posts from WordPress, to live game play from Zynga. The beauty of these external services is that they can be shared across any software platform that chooses to deploy them.

At UCSF, we recognized the value in making our research networking tool into a web platform. Accordingly, we have contributed an extension to the open-source Profiles research networking software tool, and we are now using our UCSF Profiles installation as a platform (based on the industry standard OpenSocial), whereby we have written "apps" or "gadgets" to extend the functionality. One such gadget is to display presentations, posters and other content that is uploaded to Slideshare.net, within an individual's UCSF Profile page itself. This gadget allows researchers to share conference presentations, lectures etc. easily within their UCSF research profile.

The software code for these gadgets is open source; gadgets can and have been shared with other institutions. The end goal is to create an open library of shareable gadgets for research networking, where any institution (academic, for profit etc.) can contribute to or use the apps in this library.

At this point, we think research networking software tools could make a giant leap forward by harnessing this simple technological implementation and marrying it with many institutions’ knowledge of what features and functions will enable more efficiency and collaboration in the research process. To date, one other institution using Profiles has adopted the standard and another is on track to do so in a matter of months. Wake Forest has successfully deployed Profiles as an OpenSocial enabled platform and has written 2 of their own gadgets. Baylor is now on track to do the same.

Plan: We propose to hold a competition similar to one held by VIVO in 2011. A call to institutions for the best ideas for research networking software functions would be sent out and judged on a set of criteria that would include feasibility, value and impact for enabling research efficiency and/or collaboration.

We will choose 2 winners of the competition and each would receive:

1. A new iPad 
2. Plus, development of the gadget itself, using resources from the VH team and our development network to execute. Winner would be acknowledged in attribution on gadget itself once launched.
3. Recognition via public presentation(s) at Profiles User Group meetings, as invited guest presenter at CTSA IKFC meetings etc.

With the following stipulations: a) the resulting gadget is offered in the library and made available free and open-source, 2) the winner is available as needed as subject matter expert during design and implementation of the gadget.

Impact/Value: We believe this project:

• will further the ability for research networking tools to have impact on the research process
• will contribute to the national CTSA body of knowledge and experience with research networking
• allow institutions and individuals with creative ideas for features to share those ideas with the community and contribute in a timely manner
• further demonstrate that OpenSocial is an inexpensive way to create valuable production level apps given the low technical complexity of gadgets.

Criteria: Criteria for entry would be open to all, but with active promotion to UCSF, all institutions in the Profiles User Group, all VIVO-enabled institutions.  Judges for entries would be identified from the CTSI VH team, CTSI leaders / faculty, and institutions currently leading the research networking software field (e.g., Harvard, and Wake Forest)

While we know that we may get ideas easily from IT folks, we will make a concerted effort to gather ideas from researchers themselves. In addition to soliciting the CTSI faculty (for their own ideas in addition to recommendations for others to contact), we will target those faculty who:

1)      commented on our open proposal

2)      have very well fleshed out profiles on UCSF Profiles

3)      are engaged in science of team science (we will use UCSF Profiles to identify these peopleJ)

4)      have been past proponents of UCSF Profiles

5)      have been interviewed personally by VH team members (Research Networking 2.0 interviews)

6)      are part of our post-doc user group. 

We will create a detailed description for the call for ideas. This will include the scope, i.e., new features specifically for research networking software products, and the judging criteria (to include feasibility, applicability to OpenSocial approach, value and impactfor enabling research efficiency and/or collaboration). In addition, while we plan to promote actively at UCSF, we’ll solicit entries outside of UCSF by leveraging our relationships with other institutions that are heavily engaged in adopting research networking software tools, such as the Profiles User group (including Harvard, Wake Forest, Baylor, Minnesota), Stanford CAP, VIVO (including U Illinois, U Florida), U Iowa LOKI, and the CTSA IKFC National Research Networking Group.

Total Budget: $33,406

$1000 for iPads, $32,406 for development and project management of 2 gadgets

Collaborators: Wake Forest, Harvard, CTSI leadership / faculty as judges.